{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Spatial overlays allow you to compare two GeoDataFrames containing polygon or multipolygon geometries \n",
    "and create a new GeoDataFrame with the new geometries representing the spatial combination *and*\n",
    "merged properties. This allows you to answer questions like\n",
    "\n",
    "> What are the demographics of the census tracts within 1000 ft of the highway?\n",
    "\n",
    "The basic idea is demonstrated by the graphic below but keep in mind that overlays operate at the dataframe level, \n",
    "not on individual geometries, and the properties from both are retained"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:34.256318Z",
     "start_time": "2017-12-15T21:09:34.226318Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"http://docs.qgis.org/testing/en/_images/overlay_operations.png\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.core.display import Image\n",
    "Image(url=\"http://docs.qgis.org/testing/en/_images/overlay_operations.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can load up two GeoDataFrames containing (multi)polygon geometries..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:36.236298Z",
     "start_time": "2017-12-15T21:09:34.256318Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from shapely.geometry import Point\n",
    "from geopandas import datasets, GeoDataFrame, read_file\n",
    "from geopandas.tools import overlay\n",
    "\n",
    "# NYC Boros\n",
    "zippath = datasets.get_path('nybb')\n",
    "polydf = read_file(zippath)\n",
    "\n",
    "# Generate some circles\n",
    "b = [int(x) for x in polydf.total_bounds]\n",
    "N = 10\n",
    "polydf2 = GeoDataFrame([\n",
    "    {'geometry': Point(x, y).buffer(10000), 'value1': x + y, 'value2': x - y}\n",
    "    for x, y in zip(range(b[0], b[2], int((b[2] - b[0]) / N)),\n",
    "                    range(b[1], b[3], int((b[3] - b[1]) / N)))])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first dataframe contains multipolygons of the NYC boros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:36.526295Z",
     "start_time": "2017-12-15T21:09:36.236298Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x512ee48>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAS0AAAD8CAYAAAAi9vLQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nyQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x512e2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "polydf.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And the second GeoDataFrame is a sequentially generated set of circles in the same geographic space. We'll plot these with a [different color palette](https://matplotlib.org/examples/color/colormaps_reference.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:36.756293Z",
     "start_time": "2017-12-15T21:09:36.526295Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x512e0f0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAARoAAAD8CAYAAACo2WuRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3Xl8HXW5+PHPc7Lve9p0TZekpYVSaaAFZFGgICoIAhZR\nyhXZRVC8Cvd6L/zK1R8IwrUuFBAuykUEQQF/UqGylCoUSKB0o0u6N03bNEmz7+f5/XEmeNomzUnO\nTHJy8rxfr/PK8D3zfWamaR9mvjPzfURVMcYYL/mGegeMMdHPEo0xxnOWaIwxnrNEY4zxnCUaY4zn\nLNEYYzxnicYY4zlLNMYYz1miMcZ4Lnaod8Btubm5WlhYONS7YcyIUFZWdkBV8/paL+oSTWFhIaWl\npUO9G8aMCCKyI5T17NLJGOM5SzTGGM9ZojHGeM4SjTHGc5ZojDGes0RjjPGcJRpjjOcs0RhjPBd1\nD+wZY6CzuZOW3Y20VbXQ2dSBdim+eB9x6fEkjkomcUwKvtjBO8+wRGNMFGk/2EbtB1U072yAXuoO\n1K2twRfvI216FpnH5eCLj/F8vyzRGBMFVJW6NdXUflDVa4IJ5m/3U7e6msbyOvLOGEPS6BRP98/G\naIwZ5tSvHPh7JbVloSWZYF3Nnez9604at9V7s3MOSzTGDHM1pftpLK8beACFquUVtFQ2ubdTh7FE\nY8ww1lzRSP26mvADKVQt34O/vSv8WD3oM9GIyHgReUNE1ovIOhG5xWl/RkRWOZ/tIrLKaS8UkZag\n75YExZojImtEpFxEFouIOO0JTrxyEXlXRAqD+iwUkc3OZ6HbfwDGDFfqV2re3edavK6WTg6urnYt\nXrBQBoM7gdtU9QMRSQPKRGSZqn6lewUR+SkQfO62RVVn9xDrIeAa4F3gZeA8YClwNVCrqlNFZAFw\nL/AVEckG7gRKCFx9lonIS6pa2+8jNSbKtOxupKOu3dWY9RtqyZyd6/qt7z6jqWqlqn7gLDcAHwNj\nu793zkouA54+WhwRKQDSVXWlBgp+/xb4kvP1hcBvnOXngLOcuOcCy1S1xkkuywgkJ2NGPC8GcLXD\nT8vuRtfj9ittOZc0nyJwRtLtNGCfqm4OapvkXDYtF5HTnLaxwO6gdXbzz4Q1FtgFoKqdBM6OcoLb\ne+gTvF/XikipiJRWVVX155CMGbZa9zUPm7ghJxoRSQWeB25V1eBUejmHns1UAhOcS6fvAr8TkXQ3\ndrY3qvqIqpaoakleXp/Tlxoz7Pk7/XQ1dXoS2+3LMQgx0YhIHIEk85Sq/jGoPRa4GHimu01V21S1\n2lkuA7YAxUAFMC4o7DinDefn+KCYGUB1cHsPfYwZsfzt/mEVO5S7TgI8Bnysqg8c9vXZwAZV3R20\nfp6IxDjLk4EiYKuqVgL1IjLPiXkl8KLT7SWg+47SJcDrzjjOK8B8EckSkSxgvtNmzIgmMTKsYody\n1+lU4OvAmu5b2MC/qerLwAKOHAQ+HVgkIh2AH7heVbtv9N8IPAEkEbjbtNRpfwx4UkTKgRonLqpa\nIyJ3A+876y0KimXMiOWL9yFxPrTD/bOP2JQ412NK4MQhepSUlKiVWzEjQeXSHbTudX/gNmfeKNKP\nyQ5pXREpU9WSvtazJ4ONGaaSJ6R6EjdpnPtxLdEYM0ylTslAYt0dT0kal0JcWryrMcGmiTAmInU2\nd9BW1UJXaye+WB9xmQnEZyfivLUDQExiLBkzczj40QHXtpv1KW8eD7FEY0yE6Gzq4MDbFRz8YD8t\nFUc+nRubGkf6sbnknjqWlImBR9MyZuXQvKuB9pq2sLefMSuHhNyksOP0xBKNMUNM/UrV8l1UvrwN\nf1vvb093NnZQs7KSmpWVZMzKY/ylxcRlJJB/1ngq/7KdruaBP8CXPDHNs7MZsDEaY4ZUV1snWx9Z\nTcWfyo+aZA5Xt7qKDfe8R+PWOuJS4yj4fCHxWQkD2oe04kzyzxyL+Lx7NscSjTFDxN/exdYlq6lf\nP7CpGTqbOtjyqw9p2u4kmy8UkjErJ+QH7mJT48j/7FhyTy3wNMmAXToZM2R2/3EzjVsOhhXD3+5n\n66/XMP0HJxGXFk/2nHwyZmTTWF5H064G2g+0ol3/fFbOlxBD4uhkUialkzIxzfME080SjTFDoLG8\nluq397gSq7O+nT0vlTPxihkAxCTFknFcDhnH5aCq+Fu78HcpvjgfMQneVzzoiV06GTMEKl/e5mq8\nmvf20lZ15FPCIkJMUixxqXFDlmTAEo0xg66tqpnG8vAumY6gUP1upbsxXWSJxphBNtDB3z7jrvMm\nrhss0RgzyJo9mCoToKWyCe3ybp6acFiiMWaQddSF/xRvj/xKR0OHN7HDZInGmEGmfg+nZvHbGY0x\nBohNdn9iqW4xHsYOhyUaYwZZ4uhkT+LGZSYQkxiZj8ZZojFmkKUWZXkSN63Ym7husERjzCBLnZJJ\n3ABfgDyarDmjXI/plnBqb98lIhVBNbbPD+pzh1NHe6OInBvUbrW3zYgnPmHUWRNdjZk0Lo206aHN\n8zsUBlx72/nuQVW9P3hlEZlBoIrBTGAM8DcRKVbVLqz2tolSqsqudTvYXLqRvVsqaaxtQFVJzUwl\nf9JoppxQxKTjp+CLCfy/PffUMVS/s6fHCa76TWD8pcWHzL4XafpMNE49pkpnuUFEDqm93YMLgd+r\nahuwzSmhcpKIbMepvQ0gIt21t5c6fe5y+j8H/OLw2ttOn+7a20et823MYFFVPnrtQ958chkHdvVc\njnnDO+t563evk5GfyRlXnEXJ+XPxxfgo/Jdj2fRAaVgTVgGMuWAKKZMyworhtXBrb98sIqtF5HGn\nwBv0Xi/bs9rbxgyFxtoGnvj+ozz349/1mmSC1e0/yEsPPs+jt/yS2r01JOYnM+WG2cSEUUdp1LmF\n5H92woD7D5Zwam8/BEwGZhM44/mpJ3sY2r5dKyKlIlJaVdX3L9yYcB3cV8sjN/+CLWWb+t131/od\nPPytn7N/+15SJqYz7Xsl/T4jiUmKZeKVMxjz+ckRfcnUbcC1t1V1n6p2qaofeBQ4yVm9t3rZntXe\nVtVHVLVEVUvy8ryb99QYgLaWNn57+6+p2TPwlxgbaxp44geP0ljbQEJOEkW3nMDEK2eQNC7tqP1i\nUuLIP2sCx/xwHtklowe8/cHW5xhNb7W3RaTAGb8BuAhY6yy/BPxORB4gMBhcBLynql0iUi8i8whc\nel0J/Dyoz0LgHYJqb4vIK8CPgy7L5gN3DPxwjQnf0of+zP4d+8KOU19Vx4sPPM8Vd1+F+ITsktFk\nl4ymdX8zTVsO0rq/ma4Wp9xKViLJE9JImZSBL3b4PZUy4NrbwOUiMpvA3aDtwHUAqrpORJ4F1hO4\nY3WTc8cJrPa2Geb2bauk7C/v9r1iiD7+x1q2ripn8uypn7Ql5ieTmO/N08NDJZS7Tn8HeroIfPko\nfX4E/KiH9lLg2B7aW4FLe4n1OPB4X/tpzGB4+/kVuF2v/h/PLj8k0USj4XcOZswQ6erqYt3y1a7H\n3fz+RlqbWl2PG0ks0RgTov3b9nqSEPxdfnat3+F63EhiicaYEFXvdq/G9RGxK7yLHQks0RgTotZm\n7y5v7NLJGANAbLx3k0rFxUfmPDJusURjTIgy8zM9i53hYexIYInGmBAVFI395O1rt42bHvnvK4XD\nEo0xIUpISmDKCUWuxy2YOpbMUZE7O54bLNEY0w8nXXCK6zHnXuh+zEgT3SNQxoRI/X7a91XRUV2N\ntnfgS0okPj+P2OysQ96OnnbyMUyYWcjOddtd2W7ehHxmz5/jSqxIZonGjGgtW7dT+8YKGlatwd/U\nfMT3sTlZpM/5FFlnnU58Xi4+n4+L/vUyHrr+v2lvbQ9r274YHxf/4CvExkX/P0Nx+72NoVZSUqKl\npaVDvRsmwnXW1bP3f5+loWxV3ysDxPjIPucz5F30BXxxcWx692Oe+o8n6Ors6rtvD0SEL9++gNnn\nDO+zGREpU9WSvtazMRoz4rRs28HWu+4JPckAdPmp+etr7PjxA3QcrKN47jFcec83Sc5I6ff245MS\nWHDnlcM+yfSHJRozorTu3M3O+39OV139wPrv2MXO+xbT2djIlBOKuPnXt3H82SeEPMvd9FNm8q1H\nv8vM048b0PaHK7t0MiNGV0sL2+68h44DA58Zr1vKcTMYf+sNnySYA7ur+PCVUspLN7Jv6146OwIT\njsfExpA3cRRT5xQx+5w5jJ4yJuxtR5JQL52ifxTKGMeBF152JckANK1ZT/27pWTMOxGA3HF5nHP1\n5zjn6s/h9/tpa25D/UpiSqJnD/kNJ/YnYEaEzrp6at9Y4WrMAy8uRf3+I9p9Ph9JqUkkpydbknHY\nn4IZEereeR/tDK9+0uHa9+2npXyrqzGjlSUaMyI0rV3vSdzGNd7EjTaWaMyI0Lpzd98rRVDcaNNn\nohGR8SLyhoisF5F1InKL036fiGxwKlX+SUQynfZCEWkRkVXOZ0lQrDkiskZEykVksVPKBRFJEJFn\nnPZ3nYqY3X0Wishm57PQ7T8AE/20s4uuxiZPYncO8Db5SBPKGU0ncJuqzgDmATeJyAxgGXCsqs4C\nNnFovaUtqjrb+Vwf1P4QcA2BWk9FBOpoA1wN1KrqVOBB4F4AEckG7gTmEihQd2dQjSdjQhKoceiR\nroE9GTzS9JloVLVSVT9wlhuAj4GxqvqqUycbYCWHVqE8gogUAOmqulIDD+/8FviS8/WFwG+c5eeA\ns5yznXOBZapao6q1BJLbeRjTDxIbiyTEexI7Ji3Vk7jRpl9jNM4lzacIVJoM9g3+WQwOYJJz2bRc\nRE5z2sYCwRe0u5227u92ATjJqw7ICW7voU/wflntbdMrESFhTIEnsb2KG21CTjQikkqg/vatqlof\n1P7vBC6vnnKaKoEJqjob+C6B8rjp7u3ykaz2tulLyjHFnsRN9ihutAkp0YhIHIEk85Sq/jGo/Srg\nC8AVzuUQqtqmqtXOchmwBSgGKjj08mqc04bzc7wTMxbIAKqD23voY0zIMk4+yfWYMSnJpM6a6Xrc\naBTKXSchUBv7Y1V9IKj9POD7wAWq2hzUniciMc7yZAKDvltVtRKoF5F5TswrgRedbi8B3XeULgFe\ndxLXK8B8EclyBoHnO23G9EvC2AJSZ7v7ImPWOZ/BF+ddZYRoEsq7TqcCXwfWiEj3e/X/BiwGEoBl\nzl3qlc4dptOBRSLSAfiB61W1xul3I/AEkERgTKd7XOcx4EkRKQdqgAUAqlojIncD7zvrLQqKZUa4\n1sZGNv99BTtWfUj1zp20NjQQExdLWl4+BdOnU3TKqYwunvbJi4+jFlxM08cb0bbwJqwCiB+VR855\nZ4UdZ6Swt7fNsNPSUM/fn/gfPnzpRTpaj154bfS06Zx5zbVMmTsPgPr3yqhY8j9hbd+XmMjEO75D\n4vgj7kuMODbxlYlK28tKefhrX+W9Z5/pM8kA7N24gd9/77v8+Uf/RUdbG+knzWH0VV+FEOePOZwv\nKYnxt95gSaafbJoIM2ysf/01Xlx0F/4BPCS3+q8vU1Oxm8vvf4Cs008hPi+XPY8/SWd1bcgxEicX\nMvaahcSPsjub/WWXTmZY2LX6I/73lpvxh/kG9tSTT+Gye36C+Hz429qpfeMtal9fcdR5ahILJ5A9\n/zOknzQH8dlFQDCb+MpEjfaWFl5YdFfYSQag/J23KXvhT5Rc/GV8CfHknHc22eeeRduuClq2bqej\nugbt6MCXmEj8qDySpk4mPi/XhaMY2SzRmIj33rO/p37fPtfiLf/1Ixx37nkkpAQmFhcREieMI3HC\nUd+iMWGw80AT0fydnZQ+/5yrMVsbGlj916V9r2hcY4nGRLSdH62iqTb0AdtQbXjjdddjmt5ZojER\nbdfq1Z7ErVi/zpUxHxMaSzQmotVWeDODXVdHB/X793sS2xzJEo2JaG1N3syMB9DW7F1scyhLNCai\nxSYkeBc73rvY5lCWaExEyxzt0cRSIqSPGuVNbHMESzQmoo2ZMcOTuKOmTiXOw7MlcyhLNCaiTSo5\nkbjERNfjFn/6tL5XMq6xRGMiWnxyMrM+d76rMX2xscz+4oWuxjRHZ4nGDBl/RxPtteto2fsPWipX\n0Fb9EV2tR85rduqVC4lPTnZtuyddchnpNrf0oLJ3ncygUn8HLZXLaal4nY66TcCRswfEpIwjqeAM\nksfNxxeXSlpuHud+5zb+/KO7w95+3qRJnH71N8OOY/rHEo0ZNG3VH1H/8cN0tRz9Bcmupt00lj9F\n0/YXSCv6Okljz2bWeZ+jZtdO/vHb3xy179Gk5eVx2b33ezLmY47OLp2M51SVpu0vUPvB3X0mmUP6\ndTZR//ES6tb9HPV3cMY3r+Wcm2/BFxPT730YXTyNhQ89TGaB1WEaCuHU3s4WkWVOTexlwaVqReQO\np472RhE5N6jdam+PQM07XqRh85P0dJkUitbK5dSt/TmgnHTZV7jq4V8z/vjjQ+qbkJLCGddcy8KH\nHiZj1OgBbd+Er88Z9pxStgWq+oGIpAFlBErZXgXUqOo9InI7kKWqP3Dqcj9NoFb2GOBvQLGqdonI\ne8C3CVS6fBlYrKpLReRGYJaqXi8iC4CLVPUrTu3tUqCEwN/SMmCOUx63RzbDXmRpq1lDbdn/YaBJ\nJlha0UJSCi/45L8r1q1j3WvL2PHhh1Tv3EFXe6C6QUp2DmOOOYapJ5/CjLPOJjHVytZ6xbUZ9px6\nTJXOcoOIfEygLO2FwJnOar8B3gR+4LT/XlXbgG1OCZWTRGQ7Tu1tZwe7a28vdfrc5cR6DvjF4bW3\nnT7dtbef7mu/zdBTfwf165fgRpIBaNjyNImjTiYmKXDHaOzMmYydGSjgpqp0tbfji40d0KWV8VY4\ntbdHOUkIYC/Q/Tx3b/WyPau9bSJTy94VdLXsdS+gv52mHS/0+JWIEJuQYEkmQoVdexvAqSo5ZLOc\ni8i1IlIqIqVVVVVDtRvmMC0V7k8u1VL5FurvcD2u8VY4tbf3OeM33eM43ZN79FYv27Pa26r6iKqW\nqGpJnj2IFRH8nc10HNzoelztbHaevzHDyYBrb3NoveyFHFpHe4FzJ2kSgdrb71nt7ZGls3EXgYrI\n7uto2OFJXOOdcGpv3wM8KyJXAzuAywBUdZ2IPAusBzqBm1S1u+KX1d4eIfxt7s/z+0nsdu9iG2+E\nctfp70Bv9UN7rHKuqj8CftRDeylwbA/trcClvcR6HHi8r/00kcbDIbsoK3o4EtiTwcYTvrh072LH\nexfbeMMSjfFEbOr4vlcaaOwU72Ibb1iiMZ7wxacTm1roRWDiMqe7H9d4yhKN8UzSmDNcj5mYPxdf\nbJLrcY23LNEYzySNPcflsRofKYVfcjGeGSw2H43plwN7ytm8+g0qt6+mrrqCjvZW4hNTyMwZx5hJ\nx1M0+7Nk5U0AwBebRNq0q6hbu9iVbSdPOJ+4tEJXYpnBZYnGhKRyx1pWvLiYXeU9vxlfXbmFLWuX\ns+LPi5k88zROu+Db5BZMIangDNprN9BS8WpY24/LmEZa0dfCimGGjiUac1Tq9/OPlx/i3WWPh/z8\nytZ1K9j+8TucdsG3mfOZK0if/k3QTlr2DOzdp7jM6WTNvgPxxQ2ovxl6lmhMr/z+LpY++Z9sKFva\n98pH9O1k+QsP0HBwL2dedBvpM24kLn0KDZufRLtaQ4ziI3nC+aQVfc2SzDBnicb0asVLiweUZIJ9\n8ObvSMscTclnv0by+PNIyJ9L046XaN3zJv6O+h77iC+BhFEnk1J4IXGpE8LavokMlmhMj3ZtLqP0\n9SddibXipcUUHnMyuQVTiEnIIr14IWlTv0ZHwxY6G7bjbzuI4scXl05s6njiM4qRGKsiGU0s0Zgj\nqCpv/umnrsXz+zt568WfcfH1/7z7JL4Y4jOKic8odm07JnLZczTmCBVbV7F/9wZXY25b/3dq9+90\nNaYZPizRmCNsXvU3T+Ju8iiuiXyWaMwRKrZ95EncPdtW9b2SiUqWaMwRDlbt6nulgcQ9sLvvlUxU\nskRjjtDe1uxR3BZP4prIZ4nGHCEuzpva1HHxVvN6pLJEY46QketN6az0bKt7PVJZojFHKCg8zpO4\nYwpneRLXRL5Qyq08LiL7RWRtUNszIrLK+Wzvro4gIoUi0hL03ZKgPnNEZI2IlIvIYqfkCk5Zlmec\n9nedapjdfRaKyGbnsxAzKKYed6Y3cY//rCdxTeQL5YzmCQL1rj+hql9R1dmqOptAYbk/Bn29pfs7\nVb0+qP0h4BoCdZ6KgmJeDdSq6lTgQeBeABHJBu4E5gInAXc6tZ2MxyZOn0dW/kRXY46dPJv8sfYU\n8EjVZ6JR1bcI1Fo6gnNWchnw9NFiOJUs01V1pVMY7rdA91RpFwK/cZafA85y4p4LLFPVGlWtBZZx\nWMIz/aPqp6G1ksqDH7Kr+m12V6+kquFj2jsbD1nP54vhtC/e7Oq2T7/wFlfjmeEl3HedTgP2qerm\noLZJzqVUHfBDVV0BjAWCH6LY7bTh/NwFoKqdIlIH5AS399DH9ENLew3bqt6gsraMts6e35jOSJ7I\nhJxTGZN1IjG+OKbO+gwzTvw869//S9jbP/GshYyZdHzYcczwFW6iuZxDz2YqgQmqWi0ic4AXRGRm\nmNvok4hcC1wLMGGCTSvQza9dlO/9K1v3L8OvnUddt655B2uad7Bl3zJmTbiC7NSpnLPghzTW7Wfn\npveP2vdoimefw6e/+K0B9zfRYcB3nUQkFrgYeKa7TVXbVLXaWS4DtgDFQAUwLqj7OKcN5+f4oJgZ\nQHVwew99DqGqj6hqiaqW5OXlDfSQokpHVwvvb/kl5fuW9plkgjW3V7Gy/Gdsr1pObFwCF123mBkn\nfn5A+3DCmV/l81f9GJ8vZkD9TfQI5/b22cAGVf3kkkhE8kQkxlmeTGDQd6uqVgL1IjLPGX+5EnjR\n6fYS0H1H6RLgdWcc5xVgvohkOYPA850204cufwelW5dQ3bhpgBGU9RV/YOeBvxMbl8B5X1vEBVff\n98mk433JG1vMJTc9xGcu/p4lGQOEcOkkIk8DZwK5IrIbuFNVHwMWcOQg8OnAIhHpAPzA9araPZB8\nI4E7WEnAUucD8BjwpIiUExh0XgCgqjUicjfQfd6+KCiWOYoNe/5EbdOWsOOs2/0s6cnjyUyeSNHx\nZzHluDPZsWElm1e/TuX2NdQdqKCjo5X4+GQy88YzZtIsimefzbipc3CeXjAGANEoK5heUlKipaU9\nz9Q/Ehxs3sHbm+5zLV560nhOLf5XRHo++VVVSyojmIiUqWpJX+vZk8FRZsted68u61t2sb9+Xa/f\nW5IxobBEE0XaOhvYX7+27xX7aXfNStdjmpHFEk0UqW7YiOL3Jq66H9eMHJZookhDyx5P4nb6W2lu\nr/YkthkZLNFEkbbOBs9it3sY20Q/SzRRJbruIJroYYkmisTHpg7L2Cb6WaKJImmJYzyJG+OLJyk+\nx5PYZmSwRBNFctKKAfefa8lOLcIn9iqBGThLNFEkMS6T3LRprscdlz3X9ZhmZLFEE2WmjnJ3brDU\nhNGMzpjtakwz8oQ7H43xWEdnO6s3vM3aTe+ws3IzB+ur8Pu7SEnOoCCvkGOmzGHOsZ8lIy0bgOzU\nqYzNmktF7bsubF04dvyCXt9zMiZU9lJlhOrq6mT5ey/ylzefoK7h6A/LxcTE8uk5X+BLZ19DWmoW\nnV1trCx/kPqW8CpDTiu4kCmjzgkrholu9lLlMHawvor7fv0tfvfnn/aZZKA7Kb3Af/7sCtaXv09s\nTAInTrmJjKSBzzZYNPrzTM4/e8D9jQlmiSbCVB/cy/9dch3lO1b3u29D00F+9sR3KVv7Bgmxacwr\nupWJuWfQnztRCbHpzJl0LUWjP2dvZhvX2BhNBGlrb+FnT9xG9cG9A47R5e/i0WfuIitjFJPHz2Dm\nuEuZkHMqW/e/xt66D+nyt/fYLzk+j/E5pzAx9zRiY6x0rXGXjdFEkKf//CCvvfMHV2KNyhnPXbc8\nSVxs/CdtXf4O6pp30ti2l47OZkR8JMZlkp40jpSEfDuDMf0W6hiNndFEiKqaCt549499rxiifdW7\nWP7eC5x9ymWftMX44shOnUJ26hTXtmNMKGyMJkK8sfKP+P1drsZ87e0/EG1nrGZ4skQTIT5Y96br\nMatqKti9t9z1uMb0V5+JRkQeF5H9IrI2qO0uEakQkVXO5/yg7+4QkXIR2Sgi5wa1zxGRNc53i52y\nK4hIgog847S/KyKFQX0Wishm59NdkiXqHKw/wIHaSk9iD+TulTFuC+WM5gl6rnn9oKrOdj4vA4jI\nDALlUmY6fX7VXecJeAi4hkCtp6KgmFcDtao6FXgQuNeJlQ3cCcwFTgLudOo7RZ2qWm9mxgOoqvEu\ntjGh6jPRqOpbBOotheJC4PdOxcptQDlwkogUAOmqutIpDvdb4EtBfX7jLD8HnOWc7ZwLLFPVGlWt\nBZbRc8Ib9trbWzyL3dbe6llsY0IVzhjNzSKy2rm06j7TGAvsClpnt9M21lk+vP2QPqraCdQBOUeJ\ndQQRuVZESkWktKqqKoxDGhrxcd49t5IQb8/EmKE30ETzEDAZmA1UAj91bY8GYLjX3s7L9mbCKoDc\nLO9iGxOqASUaVd2nql0aqMHxKIExFIAKYHzQquOctgpn+fD2Q/qISCyQAVQfJVbUyUjLJTtzlCex\np0481pO4xvTHgBKNM+bS7SKg+47US8AC507SJAKDvu+paiVQLyLznPGXK4EXg/p031G6BHjdGcd5\nBZgvIlnOpdl8py3qiAgnzDzT9bi5WWMYX1Dselxj+qvPJ4NF5GngTCBXRHYTuBN0pojMJjDt/nbg\nOgBVXScizwLrgU7gJlXtfgrtRgJ3sJKApc4H4DHgSREpJzDovMCJVSMidwPvO+stUtVQB6WHnc/M\nvdh5wM69Qm2fPfnL9lqBiQj2rpPHWlq72LmjmarqNtrb/MQn+MjNSWDihGSSkg6dh/d/X7yPN9/9\nkyvbzc0aw6JbnyI+LsGVeMb0xN51GkKqyvqPG1j+VhUbNjbg7+EkxeeD4uI0zjgtl2NnpiMiXHLe\njWzYUsbn89CtAAAKPklEQVTeAzvD2n6ML4arL/tPSzImYliicVlNTTtPPb2TjZsaj7qe3w8bNjSw\nYUMDxUWpXHH5eHJyUrjlqp/yk0dupLZ+YLfpRXx845L/oGjirAH1N8YL9q6Ti7Ztb+Le+zf2mWQO\nt2lzI/fev4ktWxvJyx7L7dc/TOG4Y/q9/eSkNG6+8ifMnT2/332N8ZIlGpdUVLTwy4e20NQ0sDew\nm5u7+NWSreza1UxO5mhuv+5hLv3ct0hNzuyzr88XwyknnM+iW55i1rRTBrR9Y7xkg8EuaGvr4p6f\nbKTqQM+z1/VHTk48d3x/GomJgYHitvZWVn38Fms3rWTnnk3UOlUQUpMzKMgvZPrkOZw462yyM/LD\n3rYx/WWDwYPo1b/tdyXJAFRXt/PXV/fxpQsCT/QmxCcy9/j5zD3eLofM8GWXTmFqaenizeXuvl/1\n1ooDNDV1uhrTmKFkiSZMqz46SFubew/ZAbS3+1n1UZ2rMY0ZSpZowrRhY4NHces9iWvMULBEE6Y9\ne7yZ78WruMYMBUs0YWpo9GYspb7BxmhM9LBEEyavXlm0dyFNNLFEE6bUNG+eEEjzKK4xQ8ESTZjG\nFHgzVeaYgiRP4hozFCzRhOmY6WnDKq4xQ8ESTZiOPz6TxER3/xjj433MPj7D1ZjGDCVLNGFKSozh\nzDPcnRD9jNNzSU62MRoTPexvcw/27TvI315bTWnpFrZv309dfTM+n4/c3DSKigo4Zd40zjhjJsnJ\ngYml5p89irIPDlJV1Rb2tnNz4jlvvjcTlRszVOzt7SAHDtSz5OFXeeXVVXR1Hf21grTURL761dO5\nfMGniY+PZc+eFh5cvJmWloG/jpCY4OPWb09l3LjkAccwZjCF+vb2QGtv3yciG5wCcn8SkUynvVBE\nWoJqci8J6hPRtbfffmcjV3z9Z7y89IM+kwxAQ2MrDz/yKtdc9xAVFTWMGZPEt26YSmpKTJ99e5KS\nEsNNN06xJGOi0kBrby8DjlXVWcAm4I6g77YE1eS+Pqg9YmtvL/vbR/zg9idpaOh/adrNmyu57oYl\n7NhZxcSJyfzg+9OYcUz/7hhNn5bG7f86jUmFKf3evjHDwYBqb6vqq075WoCVHFoc7giRXHt7zdqd\nLLr7DyGdxfSmpqaR2773GxobW8nKjOeG6ybzrRuncOzMdHy9/An7fDBzRjo3Xj+Zm26YTFZW/IC3\nb0ykc2Mw+BvAM0H/PUlEVhGoof1DVV1BP2pvi0i/a28PVFtbB4vufjasJNNtz54aFv/8L/zbHYFa\nStOnpTF9WhptbV3s2NlMdXU7be1+EuJ95OTEM3FCMgkJA7vMMma4CSvRiMi/EygU95TTVAlMUNVq\nEZkDvCAiM8Pcx1D241rgWoAJEyaE3O+FF9+josK9mnT/7y9lXL7g00ya9M+7RgkJMRQXpQUuFo0Z\noQb8HI2IXAV8AbjCuRxCVdtUtdpZLgO2AMV4XHtbVR9R1RJVLcnLC+2ZFlXlueffCWnd/nju+ZWu\nxzRmuBto7e3zgO8DF6hqc1B7nojEOMuTCfx/fGsk1t7esmWvq2cz3d5asZ5oe2TAmHANtPb2HUAC\nsMy5S73SucN0OrBIRDoAP3B9UL3siKq9vXZteNUge1Nd3cDevQcpKPDkBpkxw1KfiUZVL++h+bFe\n1n0eeL6X70qBY3tobwUu7aXP48Djfe3jQOyprPUiLAAVe2os0RgTZMS+69Ta6k55lJ60tXZ4FtuY\n4WjEJpqkpAQPY9szMcYEG7GJZuzY7GEZ25jhaMQmmuOODf15m/7Iz88gP9/mkjEm2IhNNIWF+Uyc\n6O48MgBnnjETsZnFjTnEiE00IsJll57iakyfT/jyxfNcjWlMNBixiQbgi18oYVJhvmvxLr5oLuPH\n57oWz5hoMaITTWxsDHfeeRnx8eG/WzqpMJ8brnf95XJjosKITjQAxUVj+K9FlxMXN/A3qUeNyuT+\n+xfabW1jejHiEw3Apz99DP/9wL+Qk9P/EifHHTeBR5ZcR8FoexLYmN5YonF86lOTeerJW7jkkpND\nupTKzUnjtu98kV/94lry8ux2tjFHY5OT96Curpk33lxL2Qdb2L69irqDTfhifOTlplNUVMC8ecXM\nm1vsytiOMcNZqJOTW6IxxgyYa1UQjDEmXJZojDGes0RjjPGcJRpjjOcs0RhjPGeJxhjjOUs0xhjP\nWaIxxnjOEo0xxnNR92SwiFQBO3r5Ohc4MIi7MxTsGKPDcDnGiara51SVUZdojkZESkN5XHo4s2OM\nDtF2jHbpZIzxnCUaY4znRlqieWSod2AQ2DFGh6g6xhE1RmOMGRoj7YzGGDMEhkWiEZFbRGStiKwT\nkVudtmwRWSYim52fWUHr3yEi5SKyUUTODWqfIyJrnO8Wi1PpTUQSROQZp/1dESkM6rPQ2cZmEVk4\nBMd5l4hUiMgq53P+cDpOEXlcRPaLyNqgtiH93YnIJGfdcqdvWLPK9+cYRaRQRFqCfp9LhsMxhk1V\nI/oDHAusBZKBWOBvwFTgJ8Dtzjq3A/c6yzOAj4AEYBKwBYhxvnsPmAcIsBT4nNN+I7DEWV4APOMs\nZwNbnZ9ZznLWIB/nXcD3elh/WBwncDpwArA2qG1If3fAs8ACZ3kJcMMgHmNh8HqHxYnYYwz778FQ\nbjzEX+KlwGNB//0fwPeBjUCB01YAbHSW7wDuCFr/FeBkZ50NQe2XAw8Hr+MsxxJ4UEqC13G+exi4\nfJCP8y56TjTD5jgP/8c1lL8757sDQKzTfjLwyiAe4yHrBa0f8ccYzmc4XDqtBU4TkRwRSQbOB8YD\no1S10llnLzDKWR4L7Arqv9tpG+ssH95+SB9V7QTqgJyjxPJCb8cJcLOIrHZO0bsvM4brccLQ/u5y\ngIPOuofHclNvxwgwyblsWi4ipwUdx3A7xpBFfKJR1Y+Be4FXgb8Cq4Cuw9ZRYFjfPjvKcT4ETAZm\nA5XAT4dqH70QDb+7vhx2jJXABFWdDXwX+J2IpA/Zzg2SiE80AKr6mKrOUdXTgVpgE7BPRAoAnJ/7\nndUr+OeZAMA4p63CWT68/ZA+IhILZADVR4nliZ6OU1X3qWqXqvqBR4GTDt/nw/Yt4o+Tof3dVQOZ\nzrqHx3JTj8eoqm2qWu0slxEYhypmeB5j6Ibyuq0f17/5zs8JwAYgE7iPQwfbfuIsz+TQAcWt9D6g\neL7TfhOHDrY96yxnA9sIDLRlOcvZg3ycBUHffwf4/XA7To4cvxjS3x3wBw4dKL1xEI8xL+iYJhNI\nANnD4RjD+vMZyo3345e4Aljv/CU8y2nLAV4DNhO4Q5MdtP6/E/g/xUackXunvYTAWMgW4Bf884HF\nROcXU+78sicH9fmG014O/MsQHOeTwBpgNfAShyaeiD9O4GkClwsdBMYKrh7q353zD/w9p/0PQMJg\nHSPwZWAdgUvjD4AvDodjDPdjTwYbYzw3LMZojDHDmyUaY4znLNEYYzxnicYY4zlLNMYYz1miMcZ4\nzhKNMcZzlmiMMZ77/2SB+rI5WiaWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12caea58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "polydf2.plot(cmap='tab20b')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `geopandas.tools.overlay` function takes three arguments:\n",
    "\n",
    "* df1\n",
    "* df2\n",
    "* how\n",
    "\n",
    "Where `how` can be one of:\n",
    "\n",
    "    ['intersection',\n",
    "    'union',\n",
    "    'identity',\n",
    "    'symmetric_difference',\n",
    "    'difference']\n",
    "\n",
    "So let's identify the areas (and attributes) where both dataframes intersect using the `overlay` tool. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:39.796263Z",
     "start_time": "2017-12-15T21:09:36.756293Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12978940>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAARwAAAD8CAYAAAClxxvWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x4dd50f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from geopandas.tools import overlay\n",
    "newdf = overlay(polydf, polydf2, how=\"intersection\")\n",
    "newdf.plot(cmap='tab20b')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And take a look at the attributes; we see that the attributes from both of the original GeoDataFrames are retained. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:40.416257Z",
     "start_time": "2017-12-15T21:09:39.796263Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BoroCode</th>\n",
       "      <th>BoroName</th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>Staten Island</td>\n",
       "      <td>330470.010332</td>\n",
       "      <td>1.623820e+09</td>\n",
       "      <td>(POLYGON ((970217.0223999023 145643.3322143555...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>Queens</td>\n",
       "      <td>896344.047763</td>\n",
       "      <td>3.045213e+09</td>\n",
       "      <td>(POLYGON ((1029606.076599121 156073.8142089844...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>741080.523166</td>\n",
       "      <td>1.937479e+09</td>\n",
       "      <td>(POLYGON ((1021176.479003906 151374.7969970703...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>359299.096471</td>\n",
       "      <td>6.364715e+08</td>\n",
       "      <td>(POLYGON ((981219.0557861328 188655.3157958984...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>464392.991824</td>\n",
       "      <td>1.186925e+09</td>\n",
       "      <td>(POLYGON ((1012821.805786133 229228.2645874023...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   BoroCode       BoroName     Shape_Leng    Shape_Area  \\\n",
       "0         5  Staten Island  330470.010332  1.623820e+09   \n",
       "1         4         Queens  896344.047763  3.045213e+09   \n",
       "2         3       Brooklyn  741080.523166  1.937479e+09   \n",
       "3         1      Manhattan  359299.096471  6.364715e+08   \n",
       "4         2          Bronx  464392.991824  1.186925e+09   \n",
       "\n",
       "                                            geometry  \n",
       "0  (POLYGON ((970217.0223999023 145643.3322143555...  \n",
       "1  (POLYGON ((1029606.076599121 156073.8142089844...  \n",
       "2  (POLYGON ((1021176.479003906 151374.7969970703...  \n",
       "3  (POLYGON ((981219.0557861328 188655.3157958984...  \n",
       "4  (POLYGON ((1012821.805786133 229228.2645874023...  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "polydf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:40.446256Z",
     "start_time": "2017-12-15T21:09:40.416257Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>value1</th>\n",
       "      <th>value2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((923175 120121, 923126.847266722 1191...</td>\n",
       "      <td>1033296</td>\n",
       "      <td>793054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POLYGON ((938595 135393, 938546.847266722 1344...</td>\n",
       "      <td>1063988</td>\n",
       "      <td>793202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POLYGON ((954015 150665, 953966.847266722 1496...</td>\n",
       "      <td>1094680</td>\n",
       "      <td>793350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POLYGON ((969435 165937, 969386.847266722 1649...</td>\n",
       "      <td>1125372</td>\n",
       "      <td>793498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POLYGON ((984855 181209, 984806.847266722 1802...</td>\n",
       "      <td>1156064</td>\n",
       "      <td>793646</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            geometry   value1  value2\n",
       "0  POLYGON ((923175 120121, 923126.847266722 1191...  1033296  793054\n",
       "1  POLYGON ((938595 135393, 938546.847266722 1344...  1063988  793202\n",
       "2  POLYGON ((954015 150665, 953966.847266722 1496...  1094680  793350\n",
       "3  POLYGON ((969435 165937, 969386.847266722 1649...  1125372  793498\n",
       "4  POLYGON ((984855 181209, 984806.847266722 1802...  1156064  793646"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "polydf2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:40.586255Z",
     "start_time": "2017-12-15T21:09:40.446256Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BoroCode</th>\n",
       "      <th>BoroName</th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>value1</th>\n",
       "      <th>value2</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>Staten Island</td>\n",
       "      <td>330470.010332</td>\n",
       "      <td>1.623820e+09</td>\n",
       "      <td>1033296</td>\n",
       "      <td>793054</td>\n",
       "      <td>POLYGON ((916755.4256330276 129447.9617643995,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>Staten Island</td>\n",
       "      <td>330470.010332</td>\n",
       "      <td>1.623820e+09</td>\n",
       "      <td>1063988</td>\n",
       "      <td>793202</td>\n",
       "      <td>POLYGON ((938595 135393, 938546.847266722 1344...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>Staten Island</td>\n",
       "      <td>330470.010332</td>\n",
       "      <td>1.623820e+09</td>\n",
       "      <td>1125372</td>\n",
       "      <td>793498</td>\n",
       "      <td>POLYGON ((961436.3049926758 175473.0296020508,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>Staten Island</td>\n",
       "      <td>330470.010332</td>\n",
       "      <td>1.623820e+09</td>\n",
       "      <td>1094680</td>\n",
       "      <td>793350</td>\n",
       "      <td>POLYGON ((954015 150665, 953966.847266722 1496...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>464392.991824</td>\n",
       "      <td>1.186925e+09</td>\n",
       "      <td>1309524</td>\n",
       "      <td>794386</td>\n",
       "      <td>POLYGON ((1043287.193237305 260300.0289916992,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   BoroCode       BoroName     Shape_Leng    Shape_Area   value1  value2  \\\n",
       "0         5  Staten Island  330470.010332  1.623820e+09  1033296  793054   \n",
       "1         5  Staten Island  330470.010332  1.623820e+09  1063988  793202   \n",
       "2         5  Staten Island  330470.010332  1.623820e+09  1125372  793498   \n",
       "3         5  Staten Island  330470.010332  1.623820e+09  1094680  793350   \n",
       "4         2          Bronx  464392.991824  1.186925e+09  1309524  794386   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((916755.4256330276 129447.9617643995,...  \n",
       "1  POLYGON ((938595 135393, 938546.847266722 1344...  \n",
       "2  POLYGON ((961436.3049926758 175473.0296020508,...  \n",
       "3  POLYGON ((954015 150665, 953966.847266722 1496...  \n",
       "4  POLYGON ((1043287.193237305 260300.0289916992,...  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newdf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's look at the other `how` operations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:44.026220Z",
     "start_time": "2017-12-15T21:09:40.586255Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12a72e48>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAARoAAAD8CAYAAACo2WuRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nxudoodFoND5HC41Go/E5/w/hJcoDL8piaQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12ae5f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "newdf = overlay(polydf, polydf2, how=\"union\")\n",
    "newdf.plot(cmap='tab20b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:47.366187Z",
     "start_time": "2017-12-15T21:09:44.026220Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12bccda0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAS0AAAD8CAYAAAAi9vLQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhTJaCoViWPH/2UAwmuqzL+4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12d79940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "newdf = overlay(polydf, polydf2, how=\"identity\")\n",
    "newdf.plot(cmap='tab20b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:50.556155Z",
     "start_time": "2017-12-15T21:09:47.366187Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12dc2710>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAARoAAAD8CAYAAACo2WuRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12d3a7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "newdf = overlay(polydf, polydf2, how=\"symmetric_difference\")\n",
    "newdf.plot(cmap='tab20b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-15T21:09:53.566125Z",
     "start_time": "2017-12-15T21:09:50.556155Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12e13630>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAS0AAAD8CAYAAAAi9vLQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKpzRcjgcUYUzWg6HI6pwRsvhcEQV/w+iixtNUc2vPQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12d3aac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "newdf = overlay(polydf, polydf2, how=\"difference\")\n",
    "newdf.plot(cmap='tab20b')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
